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Teaching Machine Learning to Design Students

  • Bram van der Vlist
  • Rick van de Westelaken
  • Christoph Bartneck
  • Jun Hu
  • Rene Ahn
  • Emilia Barakova
  • Frank Delbressine
  • Loe Feijs
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5093)

Abstract

Machine learning is a key technology to design and create intelligent systems, products, and related services. Like many other design departments, we are faced with the challenge to teach machine learning to design students, who often do not have an inherent affinity towards technology. We successfully used the Embodied Intelligence method to teach machine learning to our students. By embodying the learning system into the Lego Mindstorm NXT platform we provide the student with a tangible tool to understand and interact with a learning system. The resulting behavior of the tangible machines in combination with the positive associations with the Lego system motivated all the students. The students with less technology affinity successfully completed the course, while the students with more technology affinity excelled towards solving advanced problems. We believe that our experiences may inform and guide other teachers that intend to teach machine learning, or other computer science related topics, to design students.

Keywords

teaching machine learning design lego 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Bram van der Vlist
    • 1
  • Rick van de Westelaken
    • 1
  • Christoph Bartneck
    • 1
  • Jun Hu
    • 1
  • Rene Ahn
    • 1
  • Emilia Barakova
    • 1
  • Frank Delbressine
    • 1
  • Loe Feijs
    • 1
  1. 1.Department of Industrial DesignEindhoven University of TechnologyEindhovenThe Netherlands

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